Mechanisms of Generative AI-Generated Educational Videos on Learning Outcomes: A Review Based on Cognitive Load Theory

Main Article Content

Ruiyang Chen
Jiangxi Institute of Science and Technology, Jiangxi, China

DOI: https://doi.org/10.70267/iclpce.2026260266

Keywords

generative AI educational videos, learning outcomes, cognitive load, multimedia learning, video design optimization

Abstract

Generative AI technology has enabled end-to-end educational video generation to become a mainstream teaching medium. Nevertheless, current AI educational videos commonly suffer from excessive technical embellishment. Redundant visual elements greatly raise learners’ cognitive load, which prevents the technology from delivering its due educational value. Most existing studies focus on comparing the effects of different video formats, while the internal mechanism linking video elements to learning outcomes remains under-explored. Grounded in Cognitive Load Theory, this paper explores the relationships and operating mechanisms among elements of generative AI educational videos, cognitive load and learning outcomes. Adopting a systematic literature review method, it synthesizes cutting-edge empirical findings from China and overseas published between 2023 and 2026. The results reveal that redundant visual elements markedly increase extraneous cognitive load, while well-structured information presentation and adaptive dynamic effects can optimize the allocation of cognitive resources and boost learning performance effectively. On this basis, targeted optimization strategies are proposed. This research provides theoretical support and practical guidelines for the scientific design of AI educational videos, and facilitates the in-depth integration of generative AI and education.

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Published
Jul 15, 2026
Conference Proceedings Volume
Vol. 24 (2026): Proceedings of the 2nd International Conference on Linguistics, Psychology and Creative Education (ICLPCE 2026)
Section
Articles
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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Chen, Ruiyang. “Mechanisms of Generative AI-Generated Educational Videos on Learning Outcomes: A Review Based on Cognitive Load Theory”. Exploring Science Academic Conference Series, vol. 24, July 2026, pp. 260-6, https://doi.org/10.70267/iclpce.2026260266.